Sub-catchment-based urban flood risk assessment with a multi-index fuzzy evaluation approach: a case study of Jinjiang district, China

Urban flood risk assessment requires attention in inland areas with intensifying climate change and an increasing probability of extreme precipitation. This study describes the developments and testing of a sub-catchment-based multi-index fuzzy evaluation approach that can provide adaptation guidance for municipal decision-makers at a local level. We first built a comprehensive flood risk assessment system considering three categories: hazard, urban system, and social environment. The proposed evaluation system includes hybrid uncertain information that involves random indicator sources and hesitant fuzzy judgments from experts. The storm weather management model combined with geographic information system tools was then applied to obtain random indicators. Subsequently, hesitant fuzzy linguistic sets and the Euclidean distance method were adopted to solve the problem of uncertainty and vagueness from subjective hesitant information. Therefore, the aggregation method provides a beneficial way to assess flood risk in a hybrid uncertain environment. In addition, the proposed approach was applied to the Jinjiang district in an inland city in the P. R. of China. This supports efforts to prioritize locally tailored policies and practical measures for higher-risk sub-catchments within large urban systems

An integrated model for evaluation of big data challenges and analytical methods in recommender systems

The study aimed to present an integrated model for evaluation of big data (BD) challenges and analytical methods in recommender systems (RSs). The proposed model used fuzzy multi-criteria decision making (MCDM) which is a human judgment-based method for weighting of RSs’ properties. Human judgment is associated with uncertainty and gray information. We used fuzzy techniques to integrate, summarize, and calculate quality value judgment distances. Then, two fuzzy inference systems (FIS) are implemented for scoring BD challenges and data analytical methods in diferent RSs. In experimental testing of the proposed model, A correlation coefcient (CC) analysis is conducted to test the relationship between a BD challenge evaluation for a collaborative fltering-based RS and the results of fuzzy inference systems. The result shows the ability of the proposed model to evaluate the BD properties in RSs. Future studies may improve FIS by providing rules for evaluating BD tools

Digital Signal Processing for The Development of Deep Learning-Based Speech Recognition Technology

This research discusses digital signal processing in the context of developing deep learning-based speech recognition technology. Given the increasing demand for accurate and efficient speech recognition systems, digital signal processing techniques are essential. The research method used is an experimental method with a quantitative approach. This research method consists of several stages: introduction, research design, data collection, data preprocessing, Deep Learning Model Development, performance training and evaluation, experiments and testing, and data analysis. These findings are expected to contribute to developing more sophisticated and applicable speech recognition systems in various fields. For example, in virtual assistants such as Siri and Google Assistant, improved speech recognition accuracy will allow for more natural interactions and faster responses, improving the user experience. This technology can be used in security systems for safer and more reliable voice authentication, replacing or supplementing passwords and fingerprints. Additionally, in accessibility technology, more accurate voice recognition will be particularly beneficial for individuals with visual impairments or mobility, allowing them to control devices and access information with just voice commands. Other benefits include improvements in automated phone apps, automatic transcription for meetings or conferences, and the development of smart home devices that can be fully voice-operated

A Business Processes Reference Model for Course Document Management for Supporting Accreditation

A reference model is a fundamental starting point for the development of new information systems. Reference models are also called universal models, generic models, or model patterns. In order to obtain a higher learning programme accreditation, most of the educational institutions such as private and public universities have to clearly demonstrate that the programmes offered by them meet the quality standards established by the accreditation body. However, there is no complete and effective reference model for the business process of managing courses' document in order to support accreditation. Therefore, this master's thesis is an attempting to design a reference model, which will be as a general reference model for the business processes of managing document of courses in higher educational institutions and universities in order to obtain accreditation. As the processes to obtain the accreditation is almost similar in most universities and higher educational institutions around world, this study tries to design general business processes reference model to these process that can be as a reference for any education institutions to model its own model since the specific model is a partial model of the reference model. Moreover based on this reference model, the requirements model for Universiti Utara Malaysia (UUM)was designed and implemented as web-based system for Courses' document management supporting Accreditation. In addition to this, the purposed reference model covers all processes that are used in most universities and higher educational institutions to store, retrieve and organise the information of the courses. The methodology of this study is the general design research methodology that contained; awareness of problem, suggestion, development, evaluation, and conclusion. To evaluate the system that was designed and implemented based on the reference model, two methods was used. The first one is black box testing to ensure that the functionality specified in the requirement specification works. The other method is the questionnaire to evaluate the usability of the systems in terms of usefulness. The summary of evaluation results emphasises that this system provides an enhancement and improvement to the performance of the users to accomplish their tasks, and enables the users to complete their tasks quickly

A Customer Relationship Management (CRM) Aprroach with the Spiral Model (Case Study: Information System at Optik Sejahtera)

Optik Sejahtera is a company engaged in the sale of eye sight/ vision aids or often called glasses. In addition to glasses made of stainless and fiber, there are also many manufacturers in Indonesia that produce glasses from wood. The marketing of wood eyewear products still has problems, among which is still many people do not know about this product. This condition led to stagnant sales transactions in Optik Sejahtera. CRM (Customer Relationship Management) approach method is a marketing activity built on four pillars namely identifying, attracting, maintaining and strengthening brand loyalty, or strengthening relationships to achieve mutually beneficial goal. Therefore, information systems are required with the CRM approach method on Optik Sejahtera to increase sales transactions i.e. with spiral models. Spiral model steps are communication with customers, planning, risk analysis, engineering, construction and launch, and customer evaluation. The systems in this study use the MySQL database.  The results of this study based on analysis system of hypothesis test showed before using the system it took 8,6840 minutes and after using the system it only took 4,3197 minutes. It means, there are changes in sales transactions before and after using the information system in Optik Sejahtera. In other words, the information system on Optik Sejahtera could resulted in an increase of sales transactions. In addition, the results of the study in benefit testing obtained a percentage for utilization of 89.98%, effectiveness of 90%, and efficiency of 92.23%. This means that information systems in Optik Sejahtera using CRM approach with spiral models can increase efficiency in sales transactions

Cyber attack simulation and information fusion process refinement optimization models for cyber security

Cyber crime is an increasingly prominent threat to all aspects of society including businesses, government, banks, transportation, and individuals. The security of computer networks is dependent on the ability to recognize and defend against malicious cyber attacks. The goal of this thesis is to utilize operation research techniques to create tools that will significantly contribute to cyber security. A simulation framework and template is developed to efficiently represent computer networks and cyber security intrusion detection systems. The simulation is capable of generating complex cyber attacks based on the computer network configuration and the capabilities of the attacker. The simulation results in alert messages corresponding to attack actions and ordinary network behavior which are typically used by situational awareness tools or systems administrators to identify and take action against the attack. Through verification, validation, and an experimental performance evaluation, the simulation model is shown to be an effective tool to enable testing of situational awareness tools and for determining network vulnerabilities. In addition, this thesis extends the highly effective information fusion methods of situational awareness and threat assessment by introducing a method of adaptive process refinement for cyber security. The adaptive process refinement model utilizes integer programming optimization to improve the success of cyber attack detection, tracking, and identification. The process refinement model is designed to dynamically provide recommendations for optimal allocation of network detection resources subject to processing capacity, current attack activity, and network vulnerabilities. The cyber attack simulation methodology is utilized to create a set of attack scenarios on computer networks that are used conduct an experimental performance evaluation of the adaptive process refinement model to determine its capabilities and limitations. The simulation and process refinement methods provide operations research tools that will help to advance the field of cyber security

MS

thesisSeveral methods exist for monitoring software development. Few formal evaluation methods have been applied to measure and improve clinical software application problems once the software has been implemented in the clinical setting. A standardized software problem classification system was developed and implemented at the University of Utah Health Sciences Center. External validity was measured by a survey of 14 University Healthcare Consortium (UHC) hospitals. Internal validation was accomplished by: an indepth analysis of problems details; revision in the problem ticket format; verification from staff within the information systems department; and mapping of old problems to the new classification system. Cohen's Kappa statistics of agreement, used for reliability testing of the new classification systems, revealed good agreement (Kappa = .6162) among HELP Desk agents in consistency of classifying problems calls. A monthly quality improvement report template with the following categories was developed from the new classification system: top 25 problems; unplanned server downtimes; problem summaries; customer satisfaction survey results; top problems details; case analyses; and follow-up of case analysis. Continuous Quality Improvement (CQ) methodology was applied to problem reporting within the Office of Information Resources (OIR) and a web-based ticket entry system was implemented. The new system has resulted in the following benefits: reduction in problem resolution times by one third; improved problem ticket information; shift of 2 FTEs from call center to dispatch due to the increased efficiency of the HELP DESK; and a trend in improvement of customer satisfaction as measured by an online survey. The study provided an internal quality model for the OIR department and the UUHSC. The QM report template provided a method for tracking and trending software problems to use in conducting evaluation and quality improvement studies. The template also provided data for analysis and improvement studies. The template also provided data for analysis and improvement of customer satisfaction. The study has further potential as a model for information system departments at other health care institutions for implementing quality improvement methods. There is potential for improvement in the information technology, social, organizational, and cultural aspects as key issues emerge over time. There can be many consequences to the data collected and many consequences of change can be studied

Model-based integration testing technique using formal finite state behavioral models for component-based software

Many issues and challenges could be identified when considering integration testing of Component-Based Software Systems (CBSS). Consequently, several research have appeared in the literature, aimed at facilitating the integration testing of CBSS. Unfortunately, they suffer from a number of drawbacks and limitations such as difficulty of understanding and describing the behavior of integrated components, lack of effective formalism for test information, difficulty of analyzing and validating the integrated components, and exposing the components implementation by providing semi-formal models. Hence, these problems have made it in effective to test today’s modern complex CBSS. To address these problems, a model-based approach such as Model-Based Testing (MBT) tends to be a suitable mechanism and could be a potential solution to be applied in the context of integration testing of CBSS. Accordingly, this thesis presents a model-based integration testing technique for CBSS. Firstly, a method to extract the formal finite state behavioral models of integrated software components using Mealy machine models was developed. The extracted formal models were used to detect faulty interactions (integration bugs) or compositional problems between integrated components in the system. Based on the experimental results, the proposed method had significant impact in reducing the number of output queries required to extract the formal models of integrated software components and its performance was 50% better compared to the existing methods. Secondly, based on the extracted formal models, an effective model-based integration testing technique (MITT) for CBSS was developed. Finally, the effectiveness of the MITT was demonstrated by employing it in the air gourmet and elevator case studies, using three evaluation parameters. The experimental results showed that the MITT was effective and outperformed Shahbaz technique on the air gourmet and elevator case studies. In terms of learned components for air gourmet and elevator case studies respectively, the MITT results were better by 98.14% and 100%, output queries based on performance were 42.13% and 25.01%, and error detection capabilities were 70.62% and 75% for each of the case study

The complex problem of food safety : Applying agent-based modeling to the policy process

Many problems facing policymakers are complex and cannot be understood by reducing them to their component parts. However, many of the policy responses to complex problems continue to be based on simple, reductionist methods. Agent-based modeling (ABM) is one alternative method for informing policy that is well-suited to analyzing complex problems. ABM has practical implications for different stages of the policy process, such as testing alternatives, assisting with evaluation by setting up a counterfactual, and agenda setting. The objective of the research presented in this dissertation is to explore the opportunity for using ABM to examine complex problems of relevance for policy. To do so, three separate models were developed to investigate different aspects of food safety inspection systems. Complex problems involve interrelated feedback loops, many actors, exponential growth, asymmetric information, and uncertainty in outcomes and data, and food safety exhibits these traits, providing an interesting case study for the use of ABM. The first model explores three inspection scenarios incorporating access to information. The main finding was that the number of sick consumers is greatly reduced by giving consumers and inspectors more information about whether a retail outlet is contaminated, even if that information may be uncertain. The second model incorporated theories on risk and the role of transparency in encouraging consumer trust by giving consumers access to inspection scores. Overall, the findings were more nuanced: having access to restaurant inspection scores results in a slightly higher mean number of sick consumers, but less variation overall in the number of sick consumers. As well, a greater number of compliant restaurants results in fewer sick consumers. Rather than investigating the structure of the inspection system, the third model examines the potential for mobile technology to crowdsource information about suspected foodborne illness. This model illustrates the potential for health-oriented mobile technologies to improve the surveillance system for foodborne illness. Overall, the findings from the three models support using stylized ABMs to study various aspects of food safety inspection systems, and show that these models can be used to generate insight for policy choices and evidence-based decision making in this area

Methods and techniques of testing usability of information-retrieval systems based on the conversational model

Przedmiotem artykułu są systemy informacyjno-wyszukiwawcze oparte o model konwersacyjny, bazujące na mechanizmach tzw. czatbotów (chatbotów) definiowanych tu jako programy komputerowe umożliwiające użytkownikom prowadzenie konwersacji z systemem w języku naturalnym, wykorzystujące zaawansowane rozwiązania w zakresie sztucznej inteligencji. Celem jest określenie metod i technik skutecznej diagnozy tekstowych systemów konwersacyjnych i zaprojektowanie narzędzia służącego ich kompleksowej ewaluacji pod względem funkcjonalności, użyteczności i przyjazności dla użytkowników. Zastosowano metodę analizy i krytyki piśmiennictwa. Następnie w oparciu o analizę popularnych metod oceny użyteczności serwisów internetowych, takich jak: audyt użyteczności, testy funkcjonalne i badania user experience, zaproponowano autorski model badania użyteczności systemów konwersacyjnych dostosowany do specyfiki tego rodzaju serwisów. W rezultacie opracowano pilotażową wersję narzędzia umożliwiającego kompleksową ocenę użyteczności systemów informacyjno-wyszukiwawczych opartych o model konwersacyjny.The subject of the article is information-retrieval systems based on the conversational model, or on chatbot mechanisms, that are defined as computer programs that allow users to communicate with a system using natural language. Special attention was paid to chatbots based on advanced solutions in the field of artificial intelligence. The aim of the paper is to determine the methods and techniques for effective usability testing of conversational systems and to design a tool for their comprehensive evaluation in terms of functionality and user friendliness. The method of analysis and criticism of literature was used to determine the state of research. Then, based on the analysis of the common methods of assessing the usefulness of websites, such as the usability audit, usability tests and user experience questionnaires, authors proposed an original model of usability testing of conversational systems adapted to the specifics of this kind of services. As a result, a pilot version of a tool for chatbot usability tests was developed